$A dynamical framework for complex fractional killing$
Código QR

A dynamical framework for complex fractional killing

Abstract When chemotherapy drugs are applied to tumor cells with the same or similar genotypes, some cells are killed, while others survive. This fractional killing contributes to drug resistance in cancer. Through an incoherent feedforward loop, chemotherapy drugs not only activate p53 to induce ce...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Richard Ballweg, Andrew L. Paek, Tongli Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ae89e0aee4dd4bcc96569fe1115175e6
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:ae89e0aee4dd4bcc96569fe1115175e6
record_format	dspace
spelling	oai:doaj.org-article:ae89e0aee4dd4bcc96569fe1115175e62021-12-02T11:52:20ZA dynamical framework for complex fractional killing10.1038/s41598-017-07422-22045-2322https://doaj.org/article/ae89e0aee4dd4bcc96569fe1115175e62017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-07422-2https://doaj.org/toc/2045-2322Abstract When chemotherapy drugs are applied to tumor cells with the same or similar genotypes, some cells are killed, while others survive. This fractional killing contributes to drug resistance in cancer. Through an incoherent feedforward loop, chemotherapy drugs not only activate p53 to induce cell death, but also promote the expression of apoptosis inhibitors which inhibit cell death. Consequently, cells in which p53 is activated early undergo apoptosis while cells in which p53 is activated late survive. The incoherent feedforward loop and the essential role of p53 activation timing makes fractional killing a complex dynamical challenge, which is hard to understand with intuition alone. To better understand this process, we have constructed a representative model by integrating the control of apoptosis with the relevant signaling pathways. After the model was trained to recapture the observed properties of fractional killing, it was analyzed with nonlinear dynamical tools. The analysis suggested a simple dynamical framework for fractional killing, which predicts that cell fate can be altered in three possible ways: alteration of bifurcation geometry, alteration of cell trajectories, or both. These predicted categories can explain existing strategies known to combat fractional killing and facilitate the design of novel strategies.Richard BallwegAndrew L. PaekTongli ZhangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Richard Ballweg Andrew L. Paek Tongli Zhang A dynamical framework for complex fractional killing
description	Abstract When chemotherapy drugs are applied to tumor cells with the same or similar genotypes, some cells are killed, while others survive. This fractional killing contributes to drug resistance in cancer. Through an incoherent feedforward loop, chemotherapy drugs not only activate p53 to induce cell death, but also promote the expression of apoptosis inhibitors which inhibit cell death. Consequently, cells in which p53 is activated early undergo apoptosis while cells in which p53 is activated late survive. The incoherent feedforward loop and the essential role of p53 activation timing makes fractional killing a complex dynamical challenge, which is hard to understand with intuition alone. To better understand this process, we have constructed a representative model by integrating the control of apoptosis with the relevant signaling pathways. After the model was trained to recapture the observed properties of fractional killing, it was analyzed with nonlinear dynamical tools. The analysis suggested a simple dynamical framework for fractional killing, which predicts that cell fate can be altered in three possible ways: alteration of bifurcation geometry, alteration of cell trajectories, or both. These predicted categories can explain existing strategies known to combat fractional killing and facilitate the design of novel strategies.
format	article
author	Richard Ballweg Andrew L. Paek Tongli Zhang
author_facet	Richard Ballweg Andrew L. Paek Tongli Zhang
author_sort	Richard Ballweg
title	A dynamical framework for complex fractional killing
title_short	A dynamical framework for complex fractional killing
title_full	A dynamical framework for complex fractional killing
title_fullStr	A dynamical framework for complex fractional killing
title_full_unstemmed	A dynamical framework for complex fractional killing
title_sort	dynamical framework for complex fractional killing
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/ae89e0aee4dd4bcc96569fe1115175e6
work_keys_str_mv	AT richardballweg adynamicalframeworkforcomplexfractionalkilling AT andrewlpaek adynamicalframeworkforcomplexfractionalkilling AT tonglizhang adynamicalframeworkforcomplexfractionalkilling AT richardballweg dynamicalframeworkforcomplexfractionalkilling AT andrewlpaek dynamicalframeworkforcomplexfractionalkilling AT tonglizhang dynamicalframeworkforcomplexfractionalkilling
_version_	1718395125253537792

A dynamical framework for complex fractional killing

Ejemplares similares